Literature DB >> 19077425

The effects of misclassification in studies of gene-environment interactions.

K F Cheng1, W J Lin.   

Abstract

Differential Misclassification of genotype may cause usual tests producing spurious gene-disease associations or unable to detect important associations. To control for the resulting bias, many model-based approaches have been proposed using validation data. However, the effects of joint misclassification of genotype and environmental exposure in studies of gene-environment interaction are still not clear. In this paper, we focus on quantifying the effects of misclassification in case-control and case-only studies of interaction without specifying any model for misclassification probabilities. By using the derived results, we are able to identify important conditions, under which the presence of misclassification does not introduce bias in case-control or case-only studies. We have conducted a simulation study, using parameter values from real examples, to confirm our theoretical findings. The simulation results show that under the identified conditions, many regular tests for the hypothesis of no interaction maintain correct type I error rates in the presence of differential misclassification. However, their powers may be decreased as misclassification error rates increase. Copyright 2008 S. Karger AG, Basel.

Mesh:

Year:  2008        PMID: 19077425     DOI: 10.1159/000179556

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  7 in total

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2.  Inference for additive interaction under exposure misclassification.

Authors:  Tyler J Vanderweele
Journal:  Biometrika       Date:  2012-04-02       Impact factor: 2.445

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4.  Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error.

Authors:  Wonkuk Kim; Douglas Londono; Lisheng Zhou; Jinchuan Xing; Alejandro Q Nato; Anthony Musolf; Tara C Matise; Stephen J Finch; Derek Gordon
Journal:  Hum Hered       Date:  2013-04-11       Impact factor: 0.444

5.  Study protocol: the empirical investigation of methods to correct for measurement error in biobanks with dietary assessment.

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6.  Genotype imputation in case-only studies of gene-environment interaction: validity and power.

Authors:  Milda Aleknonytė-Resch; Silke Szymczak; Sandra Freitag-Wolf; Astrid Dempfle; Michael Krawczak
Journal:  Hum Genet       Date:  2021-05-26       Impact factor: 4.132

7.  Impact of measurement error on testing genetic association with quantitative traits.

Authors:  Jiemin Liao; Xiang Li; Tien-Yin Wong; Jie Jin Wang; Chiea Chuen Khor; E Shyong Tai; Tin Aung; Yik-Ying Teo; Ching-Yu Cheng
Journal:  PLoS One       Date:  2014-01-24       Impact factor: 3.240

  7 in total

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